In recent years, experimentation has come to the forefront of the research agenda of scholars in strategy and entrepreneurship, and it is more clearly emerging as a way to gradually solve uncertainty and produce validated learning. While theoretical work outlines that entrepreneurship – especially in the early stages – is essentially about experimentation, we are yet to understand its consequences and impact on entrepreneurs.
Throughout my research, I examine the effect of emerging practices such as accelerators, hackathons, and crowdfunding often in collaboration with government entities and incubation hubs. I have been managing research projects funded by institutions such as the UK government (Department for Business, Energy and Industrial Strategy), the Italian government (Ministry of Education, University and Research), the Strategy Research Foundation, and the Innovation Growth Lab. My work also aims to identify a set of practices that can help entrepreneurs navigate the difficult process of new venture creation.
An overview of my research work is provided below:
A Scientific Approach to Entrepreneurial
Decision-Making: Evidence from a Randomized Control Trial
With Arnaldo Camuffo, Alessandro Cordova and Alfonso Gambardella
A classical approach to collecting and elaborating information to make entrepreneurial decisions combines search heuristics such as trial and error, effectuation, and confirmatory search. This paper develops a framework for exploring the implications of a more scientific approach to entrepreneurial decision making. The panel sample of our randomized control trial includes 116 Italian startups and 16 data points over a period of about one year. Both the treatment and control groups receive 10 sessions of general training on how to obtain feedback from the market and to gauge the feasibility of their idea. We teach the treated startups to develop frameworks for predicting the performance of their idea and to conduct rigorous tests of their hypotheses, very much as scientists do in their research. We let the firms in the control group, instead, follow their intuitions about how to assess their idea, which has typically produced fairly standard search heuristics. We find that entrepreneurs who behave like scientists perform better, pivot to a greater extent to a different idea, and do not drop out less than the control group in the early stages of the startup. These results are consistent with the main prediction of our theory: a scientific approach improves precision – it reduces the odds of pursuing projects with false positive returns, and increases the odds of pursuing projects with false negative returns.
Management Science, available here
Covered by Quartz, here
Small Changes with Big Impact: Experimental Evidence of a Scientific Approach to the Decision-Making of Entrepreneurial Firms
With Arnaldo Camuffo and
Job Market Paper
Identifying the most promising business ideas is key to the introduction of novel firms, but predicting their success can be difficult. We argue that if entrepreneurs adopt a scientific approach by formulating problems clearly, developing theories about the implications of their actions, and testing these theories, they make better decisions. Our theory predicts that the scientific approach corrects the problem of overestimation and underestimation of the returns from business ideas. This has implications for important entrepreneurial choices, such as discontinuing a business idea and pivoting, as well as for performance. Using a field experiment with 251 nascent entrepreneurs attending a pre-acceleration program, we examine the effect of a scientific approach to decision-making. In the field experiment, we teach the treated group to formulate the problem scientifically and to develop and test theories about their actions, while the control group follows a standard training approach. We collect 18 data points on the decision-making and performance of all entrepreneurs for 14 months. Results show that treated entrepreneurs are more likely to close their start-up. We also find that scientific entrepreneurs are more likely to pivot a small number of times, suggesting that the scientific approach makes them more precise in pivoting to more valuable ideas. Finally, we find that the scientific approach increases revenue, suggesting that a more accurate assessment of ideas helps entrepreneurs to make better decisions and eventually leads to better performance. This study shows that the scientific approach is a critical link between decision-making and performance of nascent entrepreneurs.
Finalist, Best Conference Paper Award, SMS Minneapolis
Finalist, Research Method Award, SMS Minneapolis
Revise and resubmit, Organization Science
Latest version available here
A Scientific Approach to the Management of Entrepreneurial Firms: Evidence from a Field Experiment
With Elena Novelli
The use of systematic management practices has been shown to be key to firms’ performance, but prior research has also shown that firms often fail to employ them. This creates an interesting puzzle. Why do firms fail to adopt practices that can make them successful? We still lack a finer-grained understanding of the mechanisms through which it helps firms and their boundary conditions. The thrust of our theory is that the level of commitment to the entrepreneurial venture plays a key role in determining the success of systematic approaches to decision making. Commitment affects the effectiveness of the use of those practices and leads to higher returns in terms of performance. To test our theory, we conducted a 9-month field experiment with 259 entrepreneurs attending a strategy training program. Both treated and control entrepreneurs underwent a strategy training course, where they were exposed to key strategy concepts, but the treatment group was taught to applying these ideas with a systematic decision-making process that we label ‘a scientific approach to decision making’, formally developing theories and predictions about the problems they face and testing those predictions. Differently from prior studies, we focused on a varied sample of firms, including firms at the very beginning of their entrepreneurial journey as well as well-established firms. To ensure that subjects receiving the treatment were heavily involved in the firm’s strategic decision-making process, we focused on microbusinesses. We closely monitored both groups' decision-making processes and performance and collected data through regular telephone interviews. Results are in line with our predictions and contribute to theory and practice by shedding light on why many entrepreneurs fail to achieve superior performance.
Manuscript in preparation for submission, target: Strategic Management Journal
Nominated for Best Conference Paper Award, SMS Toronto
Academy of Management Best Paper Proceedings, 2021
A Scientific Approach to Innovation Management: Evidence from Four Field Experiments
With Arnaldo Camuffo, Alfonso Gambardella, Danilo Messinese, Elena Novelli, Emilio Paolucci
Our model shows that managers and entrepreneurs make better decisions under uncertainty if they adopt a scientific approach in which they formulate and test theories. The model predicts that they are more likely to terminate projects with negative returns, commit to projects with positive returns, or pivot to projects with higher returns. We test these implications by combining the results of four Randomized Control Trials (RCTs) involving 754 start-ups and small-medium enterprises and 10,730 data points over time. The empirical analysis corroborates the predictions of the model.
Under review, Journal of Political Economy
Latest version available here
Is Experimentation a Substitute for Experience? The Effect of Describing Planning and Experimentation on a Funding Platform
With Charlie Williams
In early-stage entrepreneurship, we argue that descriptions of activities conducted by entrepreneurs to create a new venture – both planning and especially experimentation-based activities – will be valued by resource providers as a signal of the quality and the feasibility of new ventures. We evaluate 54,337 project descriptions of entrepreneurs seeking funds on Kickstarter to provide initial evidence of the impact of planning and experimentation activities described by entrepreneurs on resource providers. Our results show that resource providers value both the description of planning and experimentation, with the latter increasing the likelihood of funding, especially for inexperienced entrepreneurs. These patterns are replicated in online experiments, suggesting that they represent true causal relationships in the observational data.
Reject and resubmit, Strategic Management Journal
What does Scientific Experimentation Mean for Entrepreneurial Performance? Evidence from a Field Experiment and Text Analysis
Recent evidence suggests that scientific experimentation is highly beneficial for entrepreneurs, but that it does not come naturally to them. Conducting experiments is, in fact, challenging for entrepreneurs, as experiments require careful design and cognitive flexibility in order to produce learning. This paper focuses on the process of experimentation that entrepreneurs go through as they assess the feasibility of their business ideas and develop them into fully-fledged start-ups, to understand what mechanisms drive the performance effects of scientific experimentation. I utilise a field experiment with early-stage entrepreneurs to identify the mechanisms behind scientific experimentation. In this field experiment with 250 early-stage entrepreneurs, half of the participants of a pre-acceleration programme learn a scientific approach to experimentation. The control group, meanwhile, attends the same course but is left free to follow a heuristic approach. I analyse the transcripts of interviews that the entrepreneurs undertake with a member of the research team to provide information about their decision-making practices, their experiments, and their performance. The treatment and control groups are balanced at baseline, but results based on content analysis of the interviews show that treated entrepreneurs display less confidence, less certainty, more precision, more analytical thinking, and more feelings of negativity compared to the control group. This study focuses on the trade-offs that entrepreneurs face between economic gains and psychological costs as they experiment and make crucial choices to develop their start-ups.
Data analysis stage
A Theory of Entrepreneurial Action:
A Scientific Approach to Entrepreneurial Decision Making
With Arnaldo Camuffo, Alfonso Gambardella, Danilo Messinese and Elena Novelli
This paper focuses on the strategic decisions nascent entrepreneurs make under conditions of uncertainty. The key agreement in the literature is that when uncertainty is high, non-predictive strategies result in superior outcomes. We introduce an adaptive type of predictive strategy – labelled a scientific approach to decision making - and show that this approach can fare well under conditions on uncertainty if the cost of articulating a prediction is low. When entrepreneurs use a scientific approach, they develop theories and hypotheses about the implications of their actions and test these theories. In using this predictive yet adaptive approach, they can make better decisions even in conditions of high uncertainty. We articulate a series of testable propositions on the implications of this approach.
Manuscript in preparation for submission, target: Academy of Management Review
Fostering a Creative Experimental Environment through Hackathons: a Field Experiment
With Shanming Liu and
While previous research has shown that entrepreneurial teams can benefit from diversity, research in this area has consistently shown that most founding teams are highly homogenous. As a result, the initial homogeneity within an entrepreneurial team can potentially limit access to heterogeneous information sources and constrain the range of viewpoints that can be generated. This is likely to hurt creative performance, which is typically observed in the initial stages of new venture foundation, when entrepreneurial teams are attempting to identify a viable business idea. In bringing together insights from literature on creativity and early-stage entrepreneurship, we are looking to gain a better understanding of what helps entrepreneurs generating and selecting viable business ideas. In order to gather causal evidence in a realistic setting, we are planning to conduct a field experiment embedded within a hackathon in November 2019.
Field experiment conducted in November 2019, data analysis stage